Roundtable: The 'popular' and African popular culture
Bibliographic record
Abstract
28 June 2013, 13:30-15:30 - Round Table: The 'popular' and African popular culture (ISCTE B2.03, Building II) This Round Table considered the work of Karin Barber, Johannes Fabian and others on ‘the popular’ and ‘popular culture’ and the continued potential of these concepts to generate original new research. What is the potential of ‘the popular’ as a vision for research of everyday life in Africa and for scholarship? What are its limits? In the light of the rise of digital media production and transformational modes of cultural production and public spheres across Africa the panel debated new developments in the field, and asked in what ways the concept of the popular has been transformed by such developments. The Round Table had a strong bearing on the overall conference theme of African dynamics in a multipolar world. Chair Filip De Boeck (Catholic University of Leuven, Belgium) Interventions Karin Barber (Centre of West African Studies, University of Birmingham) Brian Larkin (Barnard College, USA) Joyce Nyairo (Moi University, Kenya) Ato Quayson (University of Toronto) Bob White (University of Montreal)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.242 | 0.056 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".